- Paperback: 280 pages
- Publisher: Cambridge University Press; 1 edition (September 8, 2003)
- Language: English
- ISBN-10: 052152587X
- ISBN-13: 978-0521525879
- Product Dimensions: 7 x 0.7 x 9.2 inches
- Shipping Weight: 11.2 ounces (View shipping rates and policies)
- Average Customer Review: 8 customer reviews
- Amazon Best Sellers Rank: #3,504,111 in Books (See Top 100 in Books)
Enter your mobile number or email address below and we'll send you a link to download the free Kindle App. Then you can start reading Kindle books on your smartphone, tablet, or computer - no Kindle device required.
To get the free app, enter your mobile phone number.
Microarray Bioinformatics 1st Edition
Use the Amazon App to scan ISBNs and compare prices.
The Amazon Book Review
Author interviews, book reviews, editors picks, and more. Read it now
"...excellent and clearly written...concise and most informative, a pleasure to read. It should be examined by anyone interested in this means of analysis."
"The book would be ideal for biologists who wish to gain a grasp of the different analysis techniques available to the microarray user."
Society for General Microbiology
DNA microarrays have revolutionised molecular biology and are becoming a standard tool in the field. Unlike traditional molecular biology, the successful use of DNA microarrays requires a substantial use of statistics and computing, to design the arrays, design the experiments, and to analyze and manage the data. This book is written for researchers, clinicians, laboratory heads and managers, from both laboratory and bioinformatics backgrounds, who work, or intend to work with microarrays. It is a comprehensive guide to the mathematics, statistics and computing required to use microarrays successfully.
Top customer reviews
There's a lot to like here. Stekel covers everything, starting with selecting the probes and printing the arrays. Next comes raw array analysis - scanning, image processing, and measuring the effects of the array itself on the results. That covers the first six chapters. The next three go over analysis of the result, one more chapter covers experimential design, and the last chapter discusses storing, labelling, and sharing the data. Some of those topics, like experiment design, address issues that most other authors neglect.
Still, I came away feeling that I had read only half of each chapter. Going back, it turned out that I hadn't missed anything that really was there. I missed a lot, though. For example, probe selection includes a discussion of self-hybridization - good stuff. It stopped short of giving me any clear idea how much self-complementarity is too much. It mentioned DNA melting points, but without enough information for me to understand what is really melting, or how or why to choose one melting point over another. Handling of raw array data discussed Loess regression as a way to cancel out process differences across a single array. Again, it's good stuff, but what exactly is a Loess regression? Expression analysis mentions Spearman correlation as an alternative to Pearson correlation - it give Pearson's formulas, but not Spearman's. Later, when the author does give a "formula" for selecting sample sizes, it turns out to be some macro reference for some stat package. Throughout the book, I felt the same lack: I learned the names of many things, but not what they really are.
Maybe this book is OK for a first introduction. If you've had that introduction and want to take the second steps, this book probably won't meet your needs.
Example: he starts using "spot" and "feature" without making effort to explain what they mean in the context of microarrays. At times it seems he treats them as synonyms which is confusing. I consulted the index hoping to find somewhere precise definition of these terms but to no avail. At the end, I had to go to Wikipedia and various other pages which did the job but then if you have to use internet to understand the book than why not just get everything from the web and save the money for the book?
Noting that the target audience are novices in the area of microarrays (experts won't find anything valuable here), the book does a poor job of serving them. To recap: "Nice try. Could do better"
What you have to keep in mind is this book is intended for those who want a brief overview of all aspects of microarrays. Its a "forest for the trees" book on microarrays. The writing is very good and easy to follow, and its a great introductory text and reasonably priced.
Regardless of ones formal training, (e.g. Biology, Statistics, Computer Science, ... , health science) I think it would make an excellent little basic reference on ones bookshelf or to just have around in the lab for undergraduates/beginning graduate students.
Bottomline: If you prefer to learn things by starting at the start and not at the end then consider this book; Indeed its a great starter book to get your feet a little wet before jumping in over your head to the more gnarly stuff.
As a 250-pages bioinformatics book, I believe, this book is very informative and useful for microarray users and biologists who are tired of understanding the abstract biostatistic equations.